Home environment: association with hyperactivity/impulsivity in children with ADHD and theirnon-ADHD siblingscch_1345 202..212

A. Mulligan,*† R. Anney,* L. Butler,* M. O’Regan,‡ T. Richardson,*§ E. M. Tulewicz,*M. Fitzgerald* and M. Gill*

*Department of Psychiatry, Trinity College Dublin†School of Medicine and Medical Science, University College Dublin‡Department of Statistics, Trinity College Dublin, Dublin, Ireland, and§Mental Health Research and Development Unit, University of Bath, Bath, UK

Accepted for publication 17 September 2011

Keywordsattention-deficit/hyperactivity disorder,environmental factors,HOME, oppositionaldisorders

Correspondence:Aisling Mulligan, MaterMisericordiae UniversityHospital, Eccles Street,Dublin 7, IrelandE-mail:aisling.mulligan@ucd.ie

AbstractObjective We wished to ascertain if there is an association between symptoms of attention-deficit/

hyperactivity disorder (ADHD) and home environment in children with ADHD and non-ADHD

siblings, controlling for other environmental measures.

Methods 96 children with ADHD combined type (ADHD-CT) and their siblings participated in the

study. Parent and teacher Conners’ rating scales were completed and home environment was

assessed using the middle childhood and early adolescent Home Observation for Measurement of

the Environment (HOME). ADHD symptoms were assessed for correlation with HOME in children

with ADHD-CT and non-ADHD siblings and multiple regression analysis was used to control for

gender, socio-economic status, exposure to nicotine, exposure to alcohol in utero, birth weight,

gestational age, pregnancy and perinatal risk factors. The presence of oppositional disorders was

assessed for association with HOME score in those with ADHD-CT. The multiple regression analysis

was repeated controlling for environmental factors and for oppositional disorders in those with

ADHD-CT. Oppositional symptoms were assessed for correlation with HOME score in non-ADHD

siblings.

Results Teacher-rated hyperactive/impulsive scores correlated with HOME (r = -0.27, P < 0.01) in

children with ADHD-CT. This association remained significant when other environmental factors and

oppositional disorders were controlled for. Environmental factors and gender contributed to 30%

of the variance of ADHD symptoms in ADHD-CT. Parent-rated hyperactive/impulsive scores also

correlated with HOME (r = -0.28, P < 0.05) for non-ADHD siblings. An association between HOME

and diagnosis of oppositional defiant disorder or conduct disorder was found for children with

ADHD-CT and between HOME and oppositional symptoms in non-ADHD siblings.

Conclusions The home environment has a small but significant association with hyperactive/

impulsive symptoms in children with ADHD-CT and non-ADHD siblings. This association remained

when other environmental factors were taken into account. Oppositional symptoms are associated

with home environment in ADHD-CT and in non-ADHD siblings.

bs_bs_banner Child: care, health and developmentOriginal Article doi:10.1111/j.1365-2214.2011.01345.x

© 2011 Blackwell Publishing Ltd202

Introduction

Attention-deficit/hyperactivity disorder (ADHD) is character-

ized by symptoms of inattention, hyperactivity and impulsivity

before 7 years of age, with symptoms at home and school. Twin,

family and adoption studies support a genetic component to

ADHD (Schachar & Wachsmuth 1990; Frick et al. 1991; Levy

et al. 1997; Sprich et al. 2000) with heritability estimated at 76%

(Faraone et al. 2005). Molecular genetic studies have identified

several genetic variants of minor effect, many in genes involved

in monoaminergic neurotransmission (Banaschewski et al.

2010; Brookes et al. 2006). However, candidate gene studies

explain only a small amount of the genetic component of

ADHD; genome wide scan studies to date have not identified

genes of major effect (Franke et al. 2009), and the focus of

ADHD research is moving to gene–environment interactions

and endophenotype studies (Banaschewski et al. 2010).

Early child psychiatry research focused on environmental

factors. Childhood psychiatric disorders are associated with

severe marital discord, paternal psychopathology, maternal

psychiatric disorder, large family size, fostered children and

low social status (Rutter 2001). These adversity factors

(excluding fostered children) are associated with ADHD (Bie-

derman et al. 1995), and associated with ADHD after control-

ling for the effects of maternal smoking, gender and parental

ADHD (Biederman et al. 2002). A longitudinal study has

shown that family adversity predicts psychiatric disorders in

children, and in particular early onset disorder, disorders in

boys, and conduct disorders (CD) (Blanz et al. 1991). A more

recent study has shown that children with ADHD combined

type (ADHD-CT) have more risk factors for family adversity

than community controls, and that oppositional defiant symp-

toms and CD symptoms are related to family adversity factors

(Counts et al. 2005).

Adoption studies support the theory that early childhood

environment may influence the development of ADHD.

Adopted children have higher rates of ADHD than non-adopted

children (Beverly et al. 2008; Keyes et al. 2008) and those

adopted later have higher rates of ADHD (Beverly et al. 2008).

Early deprivation may have a contributory or causal role in

ADHD, as those exposed to early deprivation had higher levels

of inattention/overactivity than those with no history of depri-

vation (Kreppner et al. 2001). A meta-analysis of adoption

studies found that early deprivation was associated with exter-

nalizing symptoms (Juffer & van Ijzendoorn 2005). A signifi-

cant effect of duration of deprivation on the level of

inattention/overactivity has been shown, with effects not

attenuating over time (Kreppner et al. 2001).

We hypothesize that the quality of the home environment

might be associated with the risk of developing symptoms of

ADHD in a similar way but to a less severe effect as the effect of

early deprivation on symptoms of ADHD. In a multifactorial

model, children with a biological or genetic predisposition to

ADHD may be more vulnerable to developing ADHD in certain

home environments. Our theory has parallels with the dynamic

developmental theory of ADHD (Sagvolden et al. 2005), which

hypothesizes that altered dopaminergic function in ADHD

causes altered reinforcement of behaviour, giving rise to a failure

to inhibit certain responses and to symptoms of ADHD in some

environments; there is an interplay between the individual’s

surroundings and the biological predisposition so that symp-

toms of ADHD develop in some environments and not

in others. The aim of this study is to look for an association

between the quality of the home environment and symptoms of

ADHD and related oppositional disorders in children with

ADHD and their siblings. We expect to find a dose-dependent

association between symptoms of ADHD and the quality of the

home environment, with a more supportive home environment

associated with less symptoms of ADHD. We also expect to find

an association between the home environment and the presence

of oppositional disorders which are often associated with ADHD.

The sample is a subset of the International Multicentre

ADHD Genetics Study (IMAGE), a genetics study of 1400 fami-

lies funded by the National Institute of Mental Health (Brookes

et al. 2006). The home environment was measured using the

Home Observation for Measurement of the Environment

(HOME) (Bradley & Caldwell 1977). Other environmental

factors of known or suspected association with ADHD were

controlled for in the analysis.

Methods

Study sample

Families participating in the IMAGE study in Ireland (n = 156)

were invited to participate in this study, after ethical approval by

relevant ethics committees. Inclusion and exclusion criteria were

as for IMAGE (Brookes et al. 2006); all participating families had

a child with ADHD-CT aged 6–17 years attending a child and

adolescent child psychiatry service, a sibling in the same age

range and one or both parents available to participate in the

study. Families were excluded (following enquiry of parents) if

siblings were half siblings, adopted or fostered. Families were

excluded if the research diagnosis of ADHD-CT was not con-

firmed (n = 8), if the child with ADHD-CT or sibling had a

diagnosis of epilepsy (n = 1), autism spectrum disorder

HOME environment and ADHD 203

© 2011 Blackwell Publishing Ltd, Child: care, health and development, 39, 2, 202–212

(n = 5), IQ < 70 (n = 9) or history of a metabolic or neurological

disorder. For this study, siblings with a diagnosis of ADHD were

excluded. A total of 133 families participated in IMAGE in

Ireland; 104 of these completed the IMAGE assessment and had

a research diagnosis of ADHD-CT confirmed and did not meet

any of the exclusion criteria for IMAGE. This study commenced

some time after the IMAGE study in Ireland, recruiting 96 fami-

lies. The probands from this group did not differ significantly

from the total Irish IMAGE group in terms of ADHD severity

measured by parent and teacher Conners’ or socio-economic

status. The ADHD proband group had a mean age of 10.94 �

3.06 years, range of 5–17 years and male : female ratio of 80:16

(83% male). The sibling group had a mean age of 10.38 � 3.00

years, range of 6–17 years and male : female ratio of 43:51 (45.7%

male). There was no significant difference in the mean age of the

ADHD group and the sibling group (mean diff = 0.56; standard

error of difference = 0.44; 95% CI = -0.31–1.42; t = 1.26; P =0.21). There was a significant difference in the gender ratio of the

proband and the sibling group (chi = 29.40; d.f. = 1; P < 0.001).

Measures used

The research diagnosis of ADHD-CT was confirmed using data

from the parental account of children’s symptoms (PACS)

semi-structured interview (Chen & Taylor 2006), Conners’

rating scale data (Conners 2001) and the Strengths and Diffi-

culties Questionnaire (SDQ) (Goodman 1997). Initially all chil-

dren participating in the study (probands and siblings) were

screened for ADHD using the parent and teacher Conners’

rating scales. Those with a T-score of 63 or greater on column

‘N’ (DSM-IV Total) of the Conners’ scale were further assessed

for symptoms of ADHD using the PACS semi-structured inter-

view. The use of the cut-off point of 63 (90th percentile) on the

Conners’ T-score to identify those who were for a more detailed

assessment of ADHD symptoms using the PACS semi-

structured interview reduced the likelihood of missing a case of

ADHD, especially in the sibling group. This method of screen-

ing all child participants for ADHD was used in the IMAGE

study and facilitated a comprehensive assessment for ADHD

symptoms in all child participants. The SDQ was used to

measure clinical impairment (a requirement for the diagnosis of

ADHD) and screen for autistic spectrum disorder. Clinical

impairment was measured using the impact supplement part of

the parent and teacher SDQ. A child was considered clinically

impaired if the parent or teacher responded that the child had

difficulties in emotions, concentration, behaviour or being able

to get on with other people, and that these difficulties were

upsetting or distressing the child or interfering with the child’s

home life or friendships or classroom learning or leisure activi-

ties or peer relationships or that these difficulties were putting a

burden on the parent/teacher or the family/class as a whole.

The Hypescheme data capture system (Curran et al. 2000)

was used to extract DSM-IV symptoms from the Conners’,

PACS and SDQ data. Hence DSM-IV diagnoses of ADHD-CT,

ADHD inattentive type, ADHD hyperactive type or no ADHD

were generated, as well as oppositional defiant disorder (ODD)

and conduct disorder (CD). Four subtests of the WISC (Wech-

sler 1991) were performed (L. B.) for each child and the IQ

calculated using Sattler’s method (Sattler 1992). For this study,

ADHD symptoms were measured using the parent and teacher

Conners’ rating scale, with inattention measured using the

T-score for column L and hyperactivity/impulsivity measured

using the T-score for column M.

Probands and siblings with autistic spectrum disorder were

excluded from the sample using the Social Communication

Questionnaire (Berument et al. 1999; Rutter et al. 2003) and the

prosocial scale of the SDQ as follows. Children with a score of

15 or higher on the parent-completed Social Communication

Questionnaire, or a score of 4 or less on the parent or teacher

prosocial scale of the SDQ or for whom the researcher had a

clinical suspicion that the child may have an autism spectrum

disorder were further assessed using the autism part of the PACS

semi-structured interview. This contains 12 questions which

assess for symptoms in the three domains of autism (commu-

nication domain, reciprocal social interaction domain and

restricted, repetitive, stereotyped patterns of behaviour

domain). An algorithm applied to the autism part of the PACS

was used to classify children into those with No Autism, Atypi-

cal Autism and Typical Autism. Children identified as having

atypical autism or typical autism were then excluded from the

IMAGE study and from this study on the HOME and ADHD.

The HOME assessments were performed by the first author

with the child’s parent in the home, with the child present. The

PACS semi-structured interview was also performed at this

visit; Conners’ parent and teacher rating scales were posted to

the parent(s) approximately 10 days before the planned visit,

and were returned to the researcher either at the home visit or

immediately prior to the visit. Each HOME assessment was

performed using both interview and observation techniques, as

described in the HOME manual (Caldwell & Bradley 2001). The

manual provides guidance on the performance of the HOME,

with a comprehensive explanation of each item and some

examples for scoring HOME assessments; no other specific

training is required. Each item on the HOME is designated an

item which is rated on observation (O) or by a structured inter-

view question (I) or by either observation or structured inter-

204 A. Mulligan et al.

© 2011 Blackwell Publishing Ltd, Child: care, health and development, 39, 2, 202–212

view (E). The first author performed the HOME with the parent

with regard to the identified proband in the family. A small

subset of the sample (seven sibling pairs non-concordant for

ADHD) had HOME assessments of both the proband and

sibling. It was found that proband and sibling percentage total

HOME scores were highly correlated (r = 0.97, P < 0.001, two-

tailed) and hence no further sibling HOME assessments were

performed. The percentage HOME score of the ADHD-CT

proband was taken to represent the sibling HOME score for

statistical analysis in this study.

The middle childhood (MC) HOME was performed for those

under 10 years (Bradley et al. 1988) and contains 59 items; the early

adolescent (EA) HOME was performed for those 10 years and over

(Bradley et al. 2000) and contains 60 items which are scored positive

or negative by the rater. Hence maximum HOME scores of 59 and

60 respectively are possible. Higher HOME scores indicate an

enriched home environment. MC HOME items are grouped into

eight subscales: I Responsivity; II Encouragement of maturity; III

Emotional climate; IV Learning materials & opportunities; V

Enrichment; VI Family companianship; VII Family integration and

VIII Physical environment. The EA HOME has seven subscales: I

Physical environment; II Learning materials; III Modelling; IV Fos-

tering self-sufficiency; V Regulatory activities; VI Family compa-

nianship; VII Acceptance. The HOME has been used extensively in

research and in clinical settings (Casey & Bradley 1982; Totsika &

Sylva 2004) and has been shown to be valid in another European

population (Burston et al. 2005). Studies have shown that the

HOME has an inter-observer agreement level of 80–90% (Totsika &

Sylva 2004).

The following environmental measures were taken for chil-

dren with ADHD-CT and siblings by parental interview: expo-

sure to nicotine in utero, exposure to alcohol in utero, birth

weight, gestational age, the presence of pregnancy and perinatal

risk factors. Exposure to nicotine was measured on a 3-point

scale: no exposure (score = 0), exposure to less than 20 cigarettes

daily (score = 1), exposure to 20 cigarettes daily or more (score =2) at some time during pregnancy. Exposure to alcohol was also

measured on a 3-point scale: no exposure (score = 0), exposure to

less than 2 units per week (score = 1),exposure to 2 units per week

or greater (score = 2). Perinatal risk factors (as per IMAGE

protocol) were classified as ‘Definite Disorder’ if any of the

following factors were definitely present: birth weight less than

1.5 kg, gestational age less than 29 weeks, APGAR score less than

2 at 5 min, special care baby unit for more than 24 h, severe

infection, severe metabolic disturbance (hypoglycaemia, acido-

sis, hypocalcaemia), seizures/convulsions in the first month of

life, and as ‘Possible Disorder’ if any of these factors were sus-

pected. Pregnancy risk factors (as per IMAGE protocol) were

classified as ‘Definite Disorder’ if any of the following risk factors

listed were definitely present: antepartum haemorrhage, pre-

eclamptic toxaemia, hypertension, diabetes, severe infection,

smoking more than 20 cigarettes daily for at least 3 months of

pregnancy, use of benzodiazepines, anticonvulsants or other

drugs thought to be associated with ADHD in the offspring and

as ‘Possible Disorder’ if any of these factors were suspected. Each

parent’s socio-economic status was recorded on a 5-point scale

(professional, clerk, services/sales, labourer, other/homemaker)

according to the IMAGE protocol, and probands and siblings

donated blood or saliva samples for the IMAGE study, along with

one or both parents.

Statistical analysis

Mean HOME total and subscale scores were calculated. Each

MC or EA HOME score was converted into a percentage so the

total group of children with ADHD-CT could be studied

together, following personal communication with Robert

Bradley, an author of the HOME tool. For each child who had

the MC HOME performed, the child’s score was divided by 59

(the maximum possible MC HOME score) and multiplied by

100 to convert it to the percentage HOME score. Similarly for

each child who had the EA HOME performed, the child’s score

was divided by 60 (the maximum possible EA HOME score)

and multiplied by 100 to convert it to the percentage HOME

score. The percentage total HOME scores were assessed for cor-

relation with symptoms of hyperactivity/impulsivity and symp-

toms of inattention (parent and teacher Conners’ rating scales)

in those with ADHD-CT. Data were analysed using spss version

12. Non-parametric tests were used, as the Conners’ data were

not normally distributed. HOME subscale scores were analysed

if a significant correlation between total HOME and ADHD

symptoms was found. The group with ADHD-CT was divided

into those with and those without ODD and the mean percent-

age HOME score was compared in each group. The group with

ADHD-CT was then divided into those with and without CD

and the mean percentage HOME score was compared in each

group. Finally, multiple regression analysis was performed to

assess the effect of gender, HOME score and measured environ-

mental factors listed above on hyperactivity/impulsivity.

The analysis was repeated for their non-ADHD siblings, with

siblings excluded if they had a PACS diagnosis of ADHD or a

DSM-IV Conners’ T-score greater than 63. The percentage

HOME score of the ADHD-CT proband was taken to represent

the family HOME score and correlated with the sibling

Conners’ hyperactivity/impulsivity and inattention. Where

there was more than one non-ADHD sibling in a family, the

HOME environment and ADHD 205

© 2011 Blackwell Publishing Ltd, Child: care, health and development, 39, 2, 202–212

mean Conners’ sibling score was calculated and used for corre-

lation with the HOME score. The non-ADHD siblings’ opposi-

tional symptoms scores (parent and teacher-rated Conners’

column A T-score) were also correlated with the HOME score.

Finally, the effects of HOME and measured environmental

factors on siblings’ symptoms of ADHD were explored by per-

forming a standard multiple regression analysis.

Results

Probands

Thirty-five children with ADHD-CT had a mean total MC

HOME score of 43.1, SD = 8.0. Sixty-one early adolescents with

ADHD-CT had a mean total EA HOME score of 43.1, SD = 9.6.

The mean percentage total HOME score for the total group was

72.8, SD = 14.3, n = 96. The mean HOME subscales scores and

published mean subscale scores (Bradley et al. 1988, 2000) can

be seen in Table 1.

Higher total HOME scores were correlated with lower

teacher-rated hyperactivity/impulsivity (r = -0.27, P = 0.008,

n = 96) (see Fig. 1). There was no significant relationship

between HOME and parent-rated ADHD scores or teacher-

rated inattentive scores.

HOME subscales were correlated with teacher-rated

hyperactivity/impulsivity in those with ADHD-CT to ascertain

20.0 60.0 80.0 100.0

Percentage HOME score(early adolescent or middle childhood HOME score)

40

50

60

70

80

90

Pro

band

teac

her-

rate

d hy

pera

ctiv

e/im

puls

ive

scor

e

40.0

Figure 1. Correlation of proband teacher-rated hyperactive/impulsivescore and percentage Home Observation for Measurement of theEnvironment (HOME) score. r = -0.27, P = 0.008, n = 96. Note: a higherpercentage of HOME score (such as in the 80–100 range) indicates amore supportive home environment.

Table 1. Middle childhood (MC) and early adolescent (EA) HOME mean subscale scores in ADHD probands

n MeanStandarddeviation

Published expectedmean*

Published standarddeviation*

MC HOMEI. Responsivity 35 7.83 1.52 8.4 2.3II. Encouragement of maturity 35 5.17 1.62 4.8 1.6III. Emotional climate 35 5.43 1.54 6.0 1.6IV. Learning materials & opportunities 35 5.54 1.34 5.2 2.0V. Enrichment 35 5.34 1.76 3.4 2.2VI. Family companianship 35 5.06 1.03 4.1 1.4VII. Family integration 35 3.03 0.92 2.4 1.2VIII. Physical environment 35 5.69 1.88 6.8 1.7Total MC HOME 35 43.1 8.0 41.6 9.0

EA HOMEI. Physical environment 61 5.15 1.93 6.60 1.04II. Learning materials 61 6.90 2.61 7.98 2.01III. Modelling 61 6.21 2.05 8.00 1.68IV. Fostering self-sufficiency 61 4.67 1.30 4.16 1.31V. Regulatory activities 61 8.13 1.61 9.00 1.17VII. Family companianship 61 5.33 1.80 5.94 1.55VIII. Acceptance 61 6.62 1.85 8.69 0.77Total EA HOME 61 43.1 9.6 51.05 5.77

*Bradley and colleagues (1988, 2000).ADHD, attention-deficit/hyperactivity disorder; HOME, Home Observation for Measurement of the Environment.

206 A. Mulligan et al.

© 2011 Blackwell Publishing Ltd, Child: care, health and development, 39, 2, 202–212

if one aspect of the home environment correlated with teacher-

rated hyperactivity/impulsivity. The sample size for subscale

correlation is smaller than for correlation with the Total HOME

(n = 96), due to different MC and EA subscales. Using the MC

HOME, a negative correlation was found with physical environ-

ment (r = -0.358, P = 0.035) and with learning materials and

opportunities (r = -0.39, P = 0.021). Using the EA HOME, a

negative correlation was found with learning materials (r =-0.35, P = 0.006). In summary, children with ADHD-CT aged

less than 10 years who had a poorer physical home environ-

ment or less learning opportunities had greater teacher-rated

hyperactivity/impulsivity than those with a better physical

home environment or those with more learning opportunities.

Early adolescents with ADHD-CT who had less access to

learning materials had greater teacher-rated hyperactivity/

impulsivity than those with more access to learning materials.

Thirty-four children had ADHD-CT without ODD and had a

significantly higher mean percentage HOME score (76.93) than

the 62 children with ADHD-CT and comorbid ODD (70.48)

(mean diff = 6.46, P = 0.018, 95% CI = 1.14–11.77). Seventy-

four children had ADHD-CT without CD and had a signifi-

cantly higher mean percentage HOME score (75.58) than the 22

children with ADHD-CT and comorbid CD (63.30) (mean diff

= 12.28, P < 0.001, 95% CI = 5.83–18.72). The group with ODD

and the group with CD had less supportive home environments

than those without these comorbid disorders.

Multiple linear regression analysis was performed with

HOME score and environmental factors entered simultaneously

as independent variables and teacher-rated hyperactivity/

impulsivity as the dependent variable (see Table 2). Gender was

also entered as a predictor in the multiple regression analysis, as

the ADHD group had a significantly higher ratio of males to

females than the sibling group.

The proband group had a mean birth weight of 3.5 kg (SD =0.6 kg) and mean gestational age of 39.9 weeks (range 33–44

weeks). The majority were not exposed to nicotine in utero

(53% scored 0 vs. 29% scored 1 vs. 18% scored 2); the majority

were not exposed to alcohol in utero (52% scored 0 vs. 31%

scored 1 vs. 17% scored 2). A large proportion did not have

pregnancy risk factors as described above (39% scored 0 vs.

29.5% scored 1 vs. 31.5% scored 2); the majority did not have

perinatal risk factors (71% scored 0 vs. 16% % scored 1 vs. 13%

scored 2). All socio-economic groups were represented, with a

large proportion of fathers from socio-economic group 3

(48.4%) and from socio-economic group 4 (30.1%). Many

mothers were from socio-economic group 5 (43.6%) and from

socio-economic group 3 (35.1%).

The environmental factors and the effects of gender

explained 30% of the variance in teacher-rated hyperactivity/

impulsivity (adjusted R square = 0.307; F = 3.93 d.f. = 10, P <0.001). The regression line can be explained by the following

equation: teacher-rated hyperactive/impulsive symptoms =117.19 - 0.29 (percentage HOME score) + 1.04 (birth weight) -1.08(gestational age) + 6.40 (cig exposure) + 2.64 (alcohol

exposure) - 3.71 (pregnancy risk factors) + 3.24 (perinatal risk

factors) - 2.37 (father’s socio) + 1.56 (mother’s socio) + 11.96

(gender), using unstandardized co-efficient figures from

Table 2, with gender expressed as 1 = male and 2 = female. The

relative contribution of each variable to the regression line can

be seen from the tolerance values in Table 2; variables which

have a tolerance value of >2 or <-2 contribute more to the

equation than other environmental factors. The largest contri-

bution is from gender (tolerance = 3.1. P = 0.003), followed by

exposure to nicotine in utero (tolerance = 2.57, P = 0.013) and

by the percentage HOME score (tolerance = -2.23, P = 0.03).

Thus the percentage of HOME score and exposure to nicotine

Table 2. Regression analysis: environmental factors and teacher-rated hyperactivity/impulsivity in ADHD combined type probands

Environmental risk factors

Unstandardized coefficients Standardized coefficients

Tolerance PB Standard error Beta

(Constant) 117.189 42.150 2.780 0.007HOME score -0.286 0.128 -0.313 -2.233 0.030Birth weight 1.041 3.375 0.042 0.309 0.759Gestational age -1.083 0.956 -0.148 -1.133 0.262Cigs exposure in utero 6.396 2.489 0.362 2.570 0.013Alcohol exposure in utero 2.642 2.021 0.150 1.307 0.196Pregnancy risk factors -3.706 2.401 -0.224 -1.543 0.128Perinatal risk factors 3.239 2.361 0.166 1.372 0.176Father’s socio-economic status -2.366 1.747 -0.186 -1.355 0.181Mother’s socio-economic status 1.564 1.349 0.145 1.159 0.251Gender 11.963 3.816 0.338 3.135 0.003

ADHD, attention-deficit/hyperactivity disorder; HOME, Home Observation for Measurement of the Environment.

HOME environment and ADHD 207

© 2011 Blackwell Publishing Ltd, Child: care, health and development, 39, 2, 202–212

in utero remained significant factors which were related to

teacher-rated hyperactivity/impulsivity when other environ-

mental factors and gender were adjusted for.

Post hoc multiple regression analysis was performed control-

ling for ODD and CD as well as environmental factors listed

above. When ODD and CD were added to the model, a linear

relationship remained, with oppositional, environmental and

gender factors together describing 67% of the variance in

teacher-rated hyperactivity/impulsivity (adjusted R square =0.67, F = 7.48, d.f. = 12, P < 0.001). The relative contribution of

the HOME became greater (tolerance = -5.24, P < 0.001); the

relative contribution of paternal socio-economic status became

significant (tolerance = -2.5, P = 0.02) and the contribution of

exposure to nicotine in utero was no longer significant.

Siblings

In total, 79 families had a non-ADHD sibling or siblings who

contributed data to this analysis; 94 siblings were included in

the analysis; 23 were excluded due to a diagnosis or suspected

diagnosis of ADHD. Each family was represented only once: an

average ADHD score for all non-ADHD siblings in the family

was used. Parent-rated hyperactivity/impulsivity for siblings

correlated with the HOME score (r = -0.284, P = 0.011, n = 79)

(see Fig. 2). There was no correlation between HOME score and

parent-rated inattentiveness or teacher-rated ADHD symptoms

in siblings. HOME score correlated negatively with mean sibling

oppositional scores rated by parents (r = -0.220, P = 0.033), but

not by teachers (r = -0.191, P = 0.68).

Multiple regression analysis was performed to assess if sibling

parent-rated hyperactivity/impulsivity was predicted by mea-

sured environmental factors, including HOME score (see

Table 3). The sibling group had a mean birth weight of 3.6 kg

(SD = 0.5 kg) and mean gestational age of 39.6 weeks (range

34–43 weeks). A large proportion did not have pregnancy risk

factors (40.5% scored 0 vs. 33% scored 1 vs. 26.5% scored 2); the

majority did not have perinatal risk factors (75% scored 0 vs.

15% scored 1 vs. 10% scored 2); the majority were not exposed

to nicotine in utero (60.5% scored 0 vs. 27.5% scored 1 vs. 12%

30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0

Percentage HOME score(early adolescent or middle childhood HOME score)

40

45

50

55

60

65

70

Sib

ling

pare

nt-r

ated

hyp

erac

tive/

impu

lsiv

e sc

ore

Figure 2. Correlation of sibling parent-rated hyperactive/impulsive scoreand Home Observation for Measurement of the Environment (HOME)score r = -0.284, P = 0.011, n = 79.

Table 3. Regression analysis: environmental factors and parent-rated hyperactivity/impulsivity in non-ADHD siblings

Unstandardized coefficients Standardized coefficients

t PB Standard error Beta

(Constant) 60.321 30.126 2.002 0.052HOME score -0.160 0.089 -0.288 -1.799 0.080Birth weight 1.999 2.648 0.118 0.755 0.455Gestational age -0.270 0.654 -0.063 -0.413 0.682Cigs exposure in utero 1.934 1.865 0.185 1.037 0.306Alcohol exposure in utero -0.483 1.332 -0.054 -0.363 0.719Pregnancy risk factors 1.498 1.434 0.179 1.045 0.303Perinatal risk factors -1.348 1.672 -0.139 -0.806 0.425Father’s socio-economic status 0.739 1.108 0.118 0.666 0.509Mother’s socio-economic status 0.199 0.856 0.038 0.233 0.817Gender -0.431 2.294 -0.032 -0.188 0.852

Regression equation: parent-rated hyperactive/impulsive symptoms = 60.32 - 0.16 (percentage HOME score) + 1.99 (birth weight) - 0.27 (gestational age) + 1.93(cig exposure) - 0.48 (alcohol exposure) + 1.50 (preg risk factors) - 1.35 (perinatal risk factors) + 0.74 (father’s socio) + 0.20 (mother’s socio) - 0.43 (gender).Note: gender was expressed as 1 = male and 2 = female.ADHD, attention-deficit/hyperactivity disorder; HOME, Home Observation for Measurement of the Environment.

208 A. Mulligan et al.

© 2011 Blackwell Publishing Ltd, Child: care, health and development, 39, 2, 202–212

scored 2); the majority were not exposed to alcohol in utero

(58% scored 0 vs. 26.5% scored 1 vs. 15.5% scored 2). The

parental socio-economic groupings were the same as that of the

probands.

These environmental factors and gender in siblings predicted

just 6.5% of the variance of parent-rated hyperactivity/

impulsivity (R square = 0.256, adjusted R square = 0.065,

n = 94), with residual factors more important than gender

and the measured environmental factors. The model of gender

and environmental factors did not predict parent-rated

hyperactivity/impulsivity effectively (Regression: F = 1.339,

d.f. = 10, P = 0.245) and of the environmental factors measured,

the closest to significance was the family HOME score (see

Table 3).

Discussion

Mean HOME scores in this study (MC HOME mean = 43, SD =8.0; EA HOME mean = 43, SD = 9.6) are similar to published

means for USA samples (MC HOME mean = 42, Bradley et al.

1988; EA HOME mean = 51, Bradley et al. 2000) and a Scottish

sample (MC HOME mean = 40; EA HOME mean = 38, Burston

et al. 2005). A less supportive home environment significantly

correlated with more teacher-rated hyperactivity/impulsivity

and a greater risk of oppositional disorders in those with

ADHD-CT, and was associated with more parent-rated

hyperactivity/impulsivity and oppositionality in non-ADHD

siblings. The association between HOME score and

hyperactivity/impulsivity is in keeping with results of previous

studies which have shown that family adversity is associated

with ADHD (Biederman et al. 1995, 2002; Counts et al. 2005). A

previous longitudinal study of inattentive/hyperactive symp-

toms in children of alcoholic parents has shown that early home

environment predicts later inattention/hyperactivity (Jester

et al. 2005). In our study, we separated symptoms of ADHD into

symptoms of inattention and symptoms of hyperactivity/

impulsivity, and found that home environment is associated

with hyperactive/impulsive symptoms and not with symptoms

of inattention. It is possible that our sample size was too small to

identify an association with inattention, despite all probands

having ADHD-CT, and hence symptoms of inattention and of

hyperactivity/impulsivity. Alternatively the home environment

(in particular physical environment and learning opportuni-

ties) may influence hyperactive-impulsive symptoms but not

inattentive symptoms.

Our study also differs from previous studies on psychosocial

adversity (Biederman et al. 1995; Jester et al. 2005) as we con-

trolled for other environmental factors which could influence

symptoms of ADHD. We showed that the association between

home environment and hyperactivity/impulsivity in those with

ADHD-CT was not due to gender or measured confounding

environmental factors, nor due to comorbid oppositional dis-

orders, using multiple regression analysis. In fact the contribu-

tion of HOME score to teacher-rated hyperactivity/impulsivity

in those with ADHD-CT was greater when oppositional disor-

ders were controlled for.

It is interesting that for children with ADHD-CT, teacher-

rated hyperactivity/impulsivity correlated with HOME score

while in non-ADHD siblings, parent-rated hyperactivity/

impulsivity correlated with HOME score. The correlation with

teacher-rated hyperactivity/impulsivity in ADHD-CT is likely

to be a real finding as both the HOME and teacher-rated

symptoms were measured objectively. Parents rated children

with ADHD-CT as having more hyperactivity/impulsivity

(mean = 83.12 � 8.30, range = 59–90) than did their teachers;

(mean = 70.30 � 13.51, range = 43–90). The tighter range of

parent-rated Conners’ scores makes it more difficult for any

correlation with the HOME to be seen in the group with

ADHD-CT – a bigger sample may show a correlation between

HOME score and hyperactivity/impulsivity rated by parents as

well as teachers.

In non-ADHD siblings there was a greater range in parent-

rated hyperactivity/impulsivity (range = 41–66, mean = 48.56 �

6.28) than teacher-rated (range = 42–62, mean score = 49.03 �

5.69), and the HOME correlated with parent and not with

teacher-rated Conners’ scores. Perhaps non-ADHD children

can control any tendency towards hyperactivity/impulsivity in

the classroom but allow their ‘true selves’ to be seen at home,

where their parents can identify some children with higher

hyperactivity/impulsivity. If the study were repeated in a larger

sample of children with ADHD-CT and their siblings, there

may be a greater range of hyperactivity/impulsivity in those

with ADHD-CT at home and a greater range of hyperactivity/

impulsivity in those without ADHD in the classroom setting,

and a correlation between hyperactivity/impulsivity and

HOME may be seen in those with ADHD-CT and in their

non-ADHD siblings at home and at school.

The association between home environment and

hyperactive/impulsive symptoms is in keeping with our hypoth-

esis that the quality of the home environment is associated with

the risk of developing symptoms of ADHD, although we did

not find an association with attentional symptoms. While these

data do not prove a causal relationship, the study of children

with ADHD and their siblings allows debate on the possibility

of a causal relationship between home environment and

hyperactive/impulsive symptoms. If ADHD symptoms in

HOME environment and ADHD 209

© 2011 Blackwell Publishing Ltd, Child: care, health and development, 39, 2, 202–212

probands with ADHD-CT were causing a poor home environ-

ment, we would not expect an association between HOME score

and hyperactive/impulsive symptoms in non-ADHD siblings.

However, if a less supportive home environment was partly

causing ADHD in the child with ADHD-CT it could be

expected that a sibling brought up in the same environment

would have partial symptoms of ADHD. The affected proband

may have a greater genetic predisposition to the disorder, and

thus develop ADHD-CT while the sibling has just a few symp-

toms of the disorder.

The association between home environment and hyperac-

tivity/impulsivity in probands may be gene–environment inter-

action effect. An interaction between polymorphisms of the

DAT1 genotype and psychosocial adversity has been previously

reported in ADHD (Laucht et al. 2007) and an interaction

between severe early institutional deprivation and DAT1 geno-

type has been shown to influence symptoms of ADHD in chil-

dren adopted from Romania (Stevens et al. 2009). It would be

interesting to ascertain if there is a gene–environment interac-

tion between the current home environment (HOME) and genes

predisposing to ADHD, including DAT1.

Previous studies used Rutter’s psychosocial adversity index

(Blanz et al. 1991; Biederman et al. 2002; Counts et al. 2005)

with many measures of adversity at a societal level rather than

family level. In contrast, the HOME places particular emphasis

on how family life is adapted to the child’s developmental needs

– features which a family could modify. If we can show a

decrease in ADHD symptoms with an intervention to improve

home environment then a causal relationship will be proven.

Clinical services could then advise parents on how to provide a

more supportive home environment.

Our multiple regression analysis suggests that 30% of the

variance of hyperactivity/impulsivity in those with ADHD-CT

is due to environmental and gender factors, with a mixture of

shared and non-shared environmental factors. This is in

keeping with the finding that ADHD is 76% heritable, with

approximately 24% of the variance due to non-shared environ-

mental effects (Faraone et al. 2005). The model of environmen-

tal factors was, however, a poor predictor of hyperactivity/

impulsivity in siblings, and other factors may explain the

variance of symptoms in non-ADHD siblings better than envi-

ronmental factors.

The HOME subscale analysis highlighted the importance of a

supportive learning environment and mirrors the finding that

learning environment was consistently associated with early

motor and social developmental (Bradley et al. 2001a). Also in

younger children with ADHD, a better physical environment

and greater family integration factors were associated with less

hyperactivity/impulsivity. Hence in families with more struc-

ture (where there was a child with ADHD-CT), symptoms of

ADHD were less pronounced.

It is an advantage of this study that children with

ADHD-CT and their non-ADHD siblings were studied as the

association between hyperactivity/impulsivity and home envi-

ronment could be analysed in those with and without the dis-

order. It is also a strength that recognized research tools and

objective measures were used. It is a further strength that only

one ethnic group was studied as mean HOME scores vary for

different ethnic groups (Bradley et al. 1996, 2001b). There are

also some limitations to this study. All data are correlational so

we can only speculate on the direction of causation. The

sample size was relatively small, although the sample size was

sufficiently large to study nine independent environmental

factors using multiple regression analysis. There was some

inter-correlation of environmental variables; however, all vari-

ables studied were previously listed as of known importance in

ADHD. It is also a limitation that the groups were relatively

small when the sample with ADHD was divided into those

with and without ODD and those with and without CD.

However, despite the size of the groups, a dose-dependent

relationship was found between HOME score and the presence

of ODD and CD, with a higher mean percentage HOME score

(more supportive) in those with ODD (70.48) than those with

CD (63.30). These findings are in keeping with the study

hypothesis and in keeping with the findings of previous

studies on family adversity and oppositional disorders (Blanz

et al. 1991; Counts et al. 2005). It is a further limitation that

the HOME assessor was aware of the child’s clinical diagnosis

of ADHD and of the research hypothesis (as she devised the

study), although she was not aware if the research diagnosis of

ADHD had been confirmed or not. It may have improved the

study if the HOME was assessed separately for probands and

for siblings, although it was noted that proband and sibling

HOME scores were strongly correlated in the subset for whom

this was performed. It should be noted that it is considered

unlikely that children influence the quality of the home

environment. Robert Bradley, co-author of the HOME, stated

that ‘children whose characteristics are not extreme may have

little impact on the type or quality of experience received.

That is, they do not cause parents to reverse judgement

regarding what the child needs’ (Bradley 1994). The high cor-

relation of HOME scores in probands and siblings and the

known information about home environment makes it

unlikely that the diagnosis of ADHD in the proband could

influence the results of the HOME and ADHD symptoms

analysis for siblings.

210 A. Mulligan et al.

© 2011 Blackwell Publishing Ltd, Child: care, health and development, 39, 2, 202–212

In conclusion, a more supportive home environment was

associated with less hyperactivity/impulsivity in children with

ADHD-CT and their non-ADHD siblings. A more supportive

home environment was also associated with lower rates of ODD

and CD in those with ADHD-CT, and with lower parent-rated

oppositional scores in non-ADHD siblings. In those with

ADHD-CT, environmental factors and gender accounted for

30% of the variance of hyperactivity/impulsivity, and the

association between home environment and hyperactivity/

impulsivity remained even when gender and other environmen-

tal factors were taken into account. However, in siblings an

environmental factors and gender model did not fit the data

well, and the model of environmental factors and gender did

not explain the variance of symptoms of ADHD. A gene–

environment interaction between home environment and genes

associated with ADHD could explain the difference between

proband and sibling hyperactivity/impulsivity for siblings

brought up in the same home environment.

Key messages

• A supportive home environment is associated with less

hyperactive/impulsive symptoms in children with ADHD

and their siblings.

• A supportive home environment is associated with less

oppositional symptoms in children with ADHD and their

siblings.

Acknowledgements

We would like to thank the families who participated in this

study, especially the children. We would also like to thank child

psychiatrists of the South Western area of the Eastern Regional,

Midlands, North Eastern, South Eastern Area, and Mid Western

Areas of the Health Services Executive and to thank the Hyper-

active and Attention Deficit Disorder family support group

(HADD). We would like to acknowledge the IMAGE Consor-

tium, a multi-site, international effort supported by NIMH

grant R01MH62873 to S. Faraone.

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